A Meta-Analysis of the Faking Resistance of Forced-Choice Personality Inventories
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ABSTRACT:
SUBMITTER: Martinez A
PROVIDER: S-EPMC8511514 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. A mixed design was implemented, and predictive models were calculated. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. Relative to VR items, PIM items are shorter in length and feature no negations. Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80-83%).
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Project description:Selection methods are commonly used in talent acquisition to predict future job performance and to find the best candidates, but questionnaire-based assessments can be lengthy and lead to candidate fatigue and poor engagement, affecting completion rates and producing poor data. Gamification can mitigate some of these issues through greater engagement and shorter testing times. One avenue of gamification is image-based tests. Although such assessments are starting to gain traction in personnel selection, few studies describing their validity and psychometric properties exist. The current study explores the potential of a five-minute, forced-choice, image-based assessment of the Big Five personality traits to be used in selection. Study 1 describes the creation of the image pairs and the selection of the 150 best-performing items based on a sample of 300 respondents. Study 2 describes the creation of machine-learning-based scoring algorithms and tests of their convergent and discriminate validity and adverse impact based on a sample of 431 respondents. All models showed good levels of convergent validity with the IPIP-NEO-120 (openness r = 0.71, conscientiousness r = 0.70, extraversion r = 0.78, agreeableness r = 0.60, and emotional stability r = 0.70) and were largely free from potential adverse impact. The implications for recruitment policy and practice and the need for further validation are discussed.
| S-EPMC8883940 | biostudies-literature
Project description:How to detect faking on personality measures has been investigated using various methods and procedures. As previous findings are mixed and rarely based on ideal point item response theory models, additional research is needed for further exploration. This study modeled the responses of personality tests using ideal point method across instructed faking and honest responding conditions. A sample of undergraduate students participated the within-subjects measures to examine how the item location parameter derived from the generalized graded unfolding model changed, and how individuals' perception about items changed when faked. The mean test scores of faking group was positively correlated to the magnitude of within-subjects score change. The item-level analysis revealed both conscientiousness items (18.8%) and neuroticism items (50.0%) appeared significant shifts on item parameters, suggesting that response pattern changed from honest to faking conditions. The direction of the change appeared both in positive and negative way, demonstrating that faking could increase or decrease personality factor scores. The results indicated that the changes of perceptions on items could be operated by faking, offering some support for the ideal point model to be an adequate measure for detecting faking. However, the findings of diagnostic accuracy analysis also implied that the appropriateness of ideal point models for detecting faking should be under consideration, also be used with caution. Implications, further research directions, and limitations are discussed.
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Project description:The meta-analytic finding that faking does not affect the criterion validity of self-report measures in applicant selection suggests cognitive abilities are crucial to fake personality to an expected optimal profile in self-report measures. Previous studies in this field typically focus on how the extent of faking changes self-report measurement. However, the effect of faking ability is rarely considered. In Study 1 (n = 151), we link two questionnaires, the WSQ and the NEO-PI-R, to use them for later faking ability tasks. With O∗NET expert ratings and the linked questionnaires, we establish veridical responses of optimal personality profiles for both questionnaires. Based on this, in Study 2, we develop six faking ability task employing both questionnaires and three common jobs to fake for. To score the tasks, we introduce profile similarity metrics that compare faked response vectors to optimal profile vectors. The faking ability tasks were administered to a community sample (n = 210) who additionally completed measures of cognitive abilities, namely general mental ability, crystallized intelligence, and interpersonal abilities. For all, based on previous research, it can be argued that they should predict individual differences in faking ability. We establish a measurement model of faking ability and its relation to the other cognitive abilities. Using structural equations modeling, we find the strongest effect for crystallized intelligence and weaker effects for general mental ability and interpersonal abilities, all positively predicting faking ability. We show for the first time that we can measure faking ability with psychometrically sound techniques, establish a confirmatory factor model of faking ability and that it is largely explained by other cognitive abilities. We conclude that research supporting a positive link between self-reported personality and job performance is presumably confounded by cognitive abilities, because they are predictive of both faking self-reported personality and job performance. We recommend researchers to broaden their measurements with assessments of faking ability or other cognitive abilities (besides general mental ability) in research regarding applicant selection.
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Project description:The aim of the present study was to explore whether kinematic indicators could improve the detection of subjects demonstrating faking-good behaviour when responding to personality questionnaires. One hundred and twenty volunteers were randomly assigned to one of four experimental groups (honest unspeeded, faking-good unspeeded, honest speeded, and faking-good speeded). Participants were asked to respond to the MMPI-2 underreporting scales (L, K, S) and the PPI-R Virtuous Responding (VR) scale using a computer mouse. The collected data included T-point scores on the L, K, S, and VR scales; response times on these scales; and several temporal and spatial mouse parameters. These data were used to investigate the presence of significant differences between the two manipulated variables (honest vs. faking-good; speeded vs. unspeeded). The results demonstrated that T-scores were significantly higher in the faking-good condition relative to the honest condition; however, faking-good and honest respondents showed no statistically significant differences between the speeded and unspeeded conditions. Concerning temporal and spatial kinematic parameters, we observed mixed results for different scales and further investigations are required. The most consistent finding, albeit with small observed effects, regards the L scale, in which faking-good respondents took longer to respond to stimuli and outlined wider mouse trajectories to arrive at the given response.
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Project description:In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the direction of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation among studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Project description:Personality, or consistent individual differences in behavior, is well established in studies of dogs. Such consistency implies predictability of behavior, but some recent research suggests that predictability cannot be assumed. In addition, anecdotally, many dog experts believe that 'puppy tests' measuring behavior during the first year of a dog's life are not accurate indicators of subsequent adult behavior. Personality consistency in dogs is an important aspect of human-dog relationships (e.g., when selecting dogs suitable for substance-detection work or placement in a family). Here we perform the first comprehensive meta-analysis of studies reporting estimates of temporal consistency of dog personality. A thorough literature search identified 31 studies suitable for inclusion in our meta-analysis. Overall, we found evidence to suggest substantial consistency (r = 0.43). Furthermore, personality consistency was higher in older dogs, when behavioral assessment intervals were shorter, and when the measurement tool was exactly the same in both assessments. In puppies, aggression and submissiveness were the most consistent dimensions, while responsiveness to training, fearfulness, and sociability were the least consistent dimensions. In adult dogs, there were no dimension-based differences in consistency. There was no difference in personality consistency in dogs tested first as puppies and later as adults (e.g., 'puppy tests') versus dogs tested first as puppies and later again as puppies. Finally, there were no differences in consistency between working versus non-working dogs, between behavioral codings versus behavioral ratings, and between aggregate versus single measures. Implications for theory, practice, and future research are discussed.
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Project description:Based on the framework of testlet models, the current study suggests the Bayesian random block item response theory (BRB IRT) model to fit forced-choice formats where an item block is composed of three or more items. To account for local dependence among items within a block, the BRB IRT model incorporated a random block effect into the response function and used a Markov Chain Monte Carlo procedure for simultaneous estimation of item and trait parameters. The simulation results demonstrated that the BRB IRT model performed well for the estimation of item and trait parameters and for screening those with relatively low scores on target traits. As found in the literature, the composition of item blocks was crucial for model performance; negatively keyed items were required for item blocks. The empirical application showed the performance of the BRB IRT model was equivalent to that of the Thurstonian IRT model. The potential advantage of the BRB IRT model as a base for more complex measurement models was also demonstrated by incorporating gender as a covariate into the BRB IRT model to explain response probabilities. Recommendations for the adoption of forced-choice formats were provided along with the discussion about using negatively keyed items.
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